基于动态自适应多目标粒子群算法的企业电网无功优化

Optimal Reactive Power Dispatch of Industrial Power System Using Dynamic Adaptive Multiobjective Particle Swarm Optimization

针对大型工业企业电网无功补偿不合理、功率因数偏低、网损严重等问题,以有功网损、电压偏差、功率因数及静态电压稳定裕度为目标函数,在满足潮流方程、设备能力限制以及系统安全运行要求等约束条件下,建立了企业电网多目标无功优化模型,并提出了一种动态自适应多目标粒子群(DAMOPSO)算法进行求解.该算法通过动态变化参数增强全局搜索能力,采用动态拥挤距离保持Pareto解的多样性,同时引入自适应变异机制避免算法早熟收敛.IEEE-30节点系统和北方某大型钢铁企业电网的算例结果验证了该算法和模型的可行性和有效性.

This paper aimed at the problems of unreasonable reactive power compensation,low power factor and serious transmission losses,and established the mathematic model of multiobjective optimal reactive power dispatch for industrial power system considering four objectives including active power losses minimization,tie-line power factor maximization,voltage profile improvemen and voltage stability enhancemen while satisfying the load flow equation,equipment capability,security operation constraints and other constraints.Then a novel dynamic apdative multiobjective particle swarm optimization algorithm（DAMOPSO）was proposed to solve the optimization model,by adopting the time variant structure of parameters to improve the global search ability,the dynamic crowding distance to enhance the diversity of nondominated solutions,and the adaptive mutation operator to avoid getting trapped in local optima.The simulation results of the IEEE 30-bus system and power network of a real large iron and steel industry demonstrate the effectiveness and superiority of the prposed algorithm and model.